Interdisciplinary research is considered a source of innovativeness and creativity, serving as a key mechanism for creating recombination necessary for the evolution of science systems. The aim of this study is to quantitatively establish the connection between interdisciplinary research and the research fronts that have recently emerged in civil engineering. The degree of interdisciplinarity of the research fronts was measured by developing metrics from bibliographic analyses. As indicated by the consistent increase in the metrics of interdisciplinarity over time, research fronts tend to emerge in studies with increasing diversity in the disciplines involved. The active disciplines involved in the fronts vary over time. The most active disciplines are no longer fundamental but those associated with energy, environment, and sustainable development, focusing on solutions to climate change and integrating intelligence technologies.
In recent years, tunnel boring machines (TBMs) have been widely used in tunnel construction. However, the TBM control parameters set based on operator experience may not necessarily be suitable for certain geological conditions. Hence, a method to optimize TBM control parameters using an improved loss function-based artificial neural network (ILF-ANN) combined with quantum particle swarm optimization (QPSO) is proposed herein. The purpose of this method is to improve the TBM performance by optimizing the penetration and cutterhead rotation speeds. Inspired by the regularization technique, a custom artificial neural network (ANN) loss function based on the penetration rate and rock-breaking specific energy as TBM performance indicators is developed in the form of a penalty function to adjust the output of the network. In addition, to overcome the disadvantage of classical error backpropagation ANNs, i.e., the ease of falling into a local optimum, QPSO is adopted to train the ANN hyperparameters (weight and bias). Rock mass classes and tunneling parameters obtained in real time are used as the input of the QPSO-ILF-ANN, whereas the cutterhead rotation speed and penetration are specified as the output. The proposed method is validated using construction data from the Songhua River water conveyance tunnel project. Results show that, compared with the TBM operator and QPSO-ANN, the QPSO-ILF-ANN effectively increases the TBM penetration rate by 14.85% and 13.71%, respectively, and reduces the rock-breaking specific energy by 9.41% and 9.18%, respectively.
The present study describes a reliability analysis of the strength model for predicting concrete columns confinement influence with Fabric-Reinforced Cementitious Matrix (FRCM). through both physical models and Deep Neural Network model (artificial neural network (ANN) with double and triple hidden layers). The database of 330 samples collected for the training model contains many important parameters, i.e., section type (circle or square), corner radius rc, unconfined concrete strength fco, thickness nt, the elastic modulus of fiber Ef , the elastic modulus of mortar Em. The results revealed that the proposed ANN models well predicted the compressive strength of FRCM with high prediction accuracy. The ANN model with double hidden layers (APDL-1) was shown to be the best to predict the compressive strength of FRCM confined columns compared with the ACI design code and five physical models. Furthermore, the results also reveal that the unconfined compressive strength of concrete, type of fiber mesh for FRCM, type of section, and the corner radius ratio, are the most significant input variables in the efficiency of FRCM confinement prediction. The performance of the proposed ANN models (including double and triple hidden layers) had high precision with R higher than 0.93 and RMSE smaller than 0.13, as compared with other models from the literature available.
An approach to control the profiles of interstory drift ratios along the height of building structures via topology optimization is proposed herein. The theoretical foundation of the proposed approach involves solving a min–max optimization problem to suppress the maximum interstory drift ratio among all stories. Two formulations are suggested: one inherits the bound formulation and the other utilizes a p-norm function to aggregate all individual interstory drift ratios. The proposed methodology can shape the interstory drift ratio profiles into inverted triangular or quadratic patterns because it realizes profile control using a group of shape weight coefficients. The proposed formulations are validated via a series of numerical examples. The disparity between the two formulations is clear. The optimization results show the optimal structural features for controlling the interstory drift ratios under different requirements.
In this study, the flexural and longitudinal shear performances of two types of precast lightweight steel–ultra-high performance concrete (UHPC) composite beams are investigated, where a cluster UHPC slab (CUS) and a normal UHPC slab (NUS) are connected to a steel beam using headed studs through discontinuous shear pockets and full-length shear pockets, respectively. Results show that the longitudinal shear force of the CUS is greater than that of the NUS, whereas the interfacial slip of the former is smaller. Owing to its better integrity, the CUS exhibits greater flexural stiffness and a higher ultimate bearing capacity than the NUS. To further optimize the design parameters of the CUS, a parametric study is conducted to investigate their effects on the flexural and longitudinal shear performances. The square shear pocket is shown to be more applicable for the CUS, as the optimal spacing between two shear pockets is 650 mm. Moreover, a design method for transverse reinforcement is proposed; the transverse reinforcement is used to withstand the splitting force caused by studs in the shear pocket and prevent the UHPC slab from cracking. According to calculation results, the transverse reinforcement can be canceled when the compressive strength of UHPC is 150 MPa and the volume fraction of steel fiber exceeds 2.0%.
This paper numerically studied the effect of uncertainty and random distribution of concrete strength in beams failing in shear and flexure using lattice modeling, which is suitable for statistical analysis. The independent variables of this study included the level of strength reduction and the number of members with reduced strength. Three levels of material deficiency (i.e., 10%, 20%, 30%) were randomly introduced to 5%, 10%, 15%, and 20% of members. To provide a database and reliable results, 1000 analyses were carried out (a total of 24000 analyses) using the MATLAB software for each combination. Comparative studies were conducted for both shear- and flexure-deficit beams under four-point loading and results were compared using finite element software where relevant. Capability of lattice modeling was highlighted as an efficient tool to account for uncertainty in statistical studies. Results showed that the number of deficient members had a more significant effect on beam capacity compared to the level of strength deficiency. The scatter of random load-capacities was higher in flexure (range: 0.680–0.990) than that of shear (range: 0.795–0.996). Finally, nonlinear regression relationships were established with coefficient of correlation values (R2) above 0.90, which captured the overall load–deflection response and level of load reduction.
Reinforced concrete structural walls are commonly used for resisting lateral forces in buildings. Owing to the advancements in the field of concrete materials over the past few decades, concrete mixes of high compressive strength, commonly referred to as high-strength concrete (HSC), have been developed. In this study, the effects of strategic placement of HSC on the performance of slender walls were examined. The finite-element model of a conventional normal-strength concrete (NSC) prototype wall was validated using test data available in extant studies. HSC was incorporated in the boundary elements of the wall to compare its performance with that of the conventional wall at different axial loads. Potential reductions in the reinforcement area and size of the boundary elements were investigated. The HSC wall exhibited improved strength and stiffness, and thereby, allowed reduction in the longitudinal reinforcement area and size of the boundary elements for the same strength of the conventional wall. Cold joints resulting from dissimilar concrete pours in the web and boundary elements of the HSC wall were modeled and their impact on behavior of the wall was examined.
This paper addresses the potential use of Sugar Cane Bagasse Ash (SCBA) as a pozzolanic material for partial cement replacement in concrete mixtures. Cement mortars containing SCBA having five different particle size distributions at a replacement rate of 20% by weight were used to study the chemical and physical pozzolanic properties of SCBA. The durability of SCBA replaced mortars was also evaluated. SCBA with 0% retained on sieve No. 325 was used to replace 20% by weight of cement and create mortar specimens that were subjected to sulfuric acid attack of varying concentrations (1%−3% by weight of water). The tested samples were observed to check visual distortion, mass loss, and compressive strength loss at 1, 7, 14, 28, and 56 d of acidic exposure, and the results were compared to those for the control sample, that was lime water cured, at the same ages. The SCBA sets were found to meet the requirements for pozzolan class N specified by ASTM C 618. Mortars containing SCBA with 0% or 15% retention produced better compressive strength than the control mortars after 28 d. Additionally, X-ray fluorescence and X-ray diffraction analysis showed that the SCBA had favorable chemical properties for a pozzolanic material. Furthermore, SCBA replaced samples at all ages showed improved resistance against acidic attack relative to that of the control mortars. Maximum deterioration was seen for 3% concentrated solution. This study’s findings demonstrated that SCBA with an appropriate fineness could be used as a pozzolanic material, consistently with ASTM C 618.
The prediction of structural performance plays a significant role in damage assessment of glass fiber reinforcement polymer (GFRP) elastic gridshell structures. Machine learning (ML) approaches are implemented in this study, to predict maximum stress and displacement of GFRP elastic gridshell structures. Several ML algorithms, including linear regression (LR), ridge regression (RR), support vector regression (SVR), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), category boosting (CatBoost), and light gradient boosting machine (LightGBM), are implemented in this study. Output features of structural performance considered in this study are the maximum stress as f1(x) and the maximum displacement to self-weight ratio as f2(x). A comparative study is conducted and the Catboost model presents the highest prediction accuracy. Finally, interpretable ML approaches, including shapely additive explanations (SHAP), partial dependence plot (PDP), and accumulated local effects (ALE), are applied to explain the predictions. SHAP is employed to describe the importance of each variable to structural performance both locally and globally. The results of sensitivity analysis (SA), feature importance of the CatBoost model and SHAP approach indicate the same parameters as the most significant variables for f1(x) and f2(x).
The interactions between reinforced concrete (RC) frames and infill walls play an important role in the seismic response of frames, particularly for low-rise frames. Infill walls can increase the overall lateral strength and stiffness of the frame owing to their high strength and stiffness. However, local wall-frame interactions can also lead to increased shear demand in the columns owing to the compressive diagonal strut force from the inﬁll wall, which can result in failure or in serious situations, collapse. In this study, the effectiveness of a design strategy to consider the complex infill wall interaction was investigated. The approach was used to design example RC frames with infill walls in locations with different seismicity levels in Thailand. The performance of these frames was assessed using nonlinear static, and dynamic analyses. The performance of the frames and the failure modes were compared with those of frames designed without considering the infill wall or the local interactions. It was found that even though the overall responses of the buildings designed with and without consideration of the local interaction of the infill walls were similar in terms the overall lateral strength, the failure modes were different. The proposed method can eliminate the column shear failure from the building. Finally, the merits and limitations of this approach are discussed and summarized.
A numerical framework was proposed for the seismic analysis of underground structures in layered ground under inclined P-SV waves. The free-field responses are first obtained using the stiffness matrix method based on plane-wave assumptions. Then, the domain reduction method was employed to reproduce the wavefield in the numerical model of the soil–structure system. The proposed numerical framework was verified by providing comparisons with analytical solutions for cases involving free-field responses of homogeneous ground, layered ground, and pressure-dependent heterogeneous ground, as well as for an example of a soil–structure interaction simulation. Compared with the viscous and viscous-spring boundary methods adopted in previous studies, the proposed framework exhibits the advantage of incorporating oblique incident waves in a nonlinear heterogeneous ground. Numerical results show that SV-waves are more destructive to underground structures than P-waves, and the responses of underground structures are significantly affected by the incident angles.
Fiber-reinforced self-compacting concrete (FRSCC) is a typical construction material, and its compressive strength (CS) is a critical mechanical property that must be adequately determined. In the machine learning (ML) approach to estimating the CS of FRSCC, the current research gaps include the limitations of samples in databases, the applicability constraints of models owing to limited mixture components, and the possibility of applying recently proposed models. This study developed different ML models for predicting the CS of FRSCC to address these limitations. Artificial neural network, random forest, and categorical gradient boosting (CatBoost) models were optimized to derive the best predictive model with the aid of a 10-fold cross-validation technique. A database of 381 samples was created, representing the most significant FRSCC dataset compared with previous studies, and it was used for model development. The findings indicated that CatBoost outperformed the other two models with excellent predictive abilities (root mean square error of 2.639 MPa, mean absolute error of 1.669 MPa, and coefficient of determination of 0.986 for the test dataset). Finally, a sensitivity analysis using a partial dependence plot was conducted to obtain a thorough understanding of the effect of each input variable on the predicted CS of FRSCC. The results showed that the cement content, testing age, and superplasticizer content are the most critical factors affecting the CS.
This paper presents a novel approach for simulating the localized leakage behavior of segmentally lined tunnels based on a cohesive zone model. The proposed approach not only simulates localized leakage at the lining segment, but also captures the hydromechanically coupled seepage behavior at the segmental joints. It is first verified via a tunnel drainage experiment, which reveals its merits over the existing local hydraulic conductivity method. Subsequently, a parametric study is conducted to investigate the effects of the aperture size, stratum permeability, and spatial distribution of drainage holes on the leakage behavior, stratum seepage field, and leakage-induced mechanical response of the tunnel lining. The proposed approach yields more accurate results than the classical local hydraulic conductivity method. Moreover, it is both computationally efficient and stable. Localized leakage leads to reduced local ground pressure, which further induces outward deformation near the leakage point and slight inward deformation at its diametrically opposite side. A localized stress arch spanning across the leakage point is observed, which manifests as the rotation of the principal stresses in the adjacent area. The seepage field depends on both the number and location of the leakage zones. Pseudostatic seepage zones, in which the seepage rate is significantly lower than that of the adjacent area, appear when multiple seepage zones are considered. Finally, the importance of employing the hydromechanical coupled mechanism at the segment joints is highlighted by cases of shallowly buried tunnels subjected to surface loading and pressure tunnels while considering internal water pressure.
The present study proposes the mix design method of Fly Ash (FA) based geopolymer concrete using Response Surface Methodology (RSM). In this method, different factors, including binder content, alkali/binder ratio, NS/NH ratio (sodium silicate/sodium hydroxide), NH molarity, and water/solids ratio were considered for the mix design of geopolymer concrete. The 2D contour plots were used to setup the mix design method to achieve the target compressive strength. The proposed mix design method of geopolymer concrete is divided into three categories based on curing regime, specifically one ambient curing (25 °C) and two heat curing (60 and 90 °C). The proposed mix design method of geopolymer concrete was validated through experimentation of M30, M50, and M70 concrete mixes at all curing regimes. The observed experimental compressive strength results validate the mix design method by more than 90% of their target strength. Furthermore, the current study concluded that the required compressive strength can be achieved by varying any factor in the mix design. In addition, the factor analysis revealed that the NS/NH ratio significantly affects the compressive strength of geopolymer concrete.
Blasting engineering in complex urban environments is considered to influence the safety and stability of the overlying drainage box culvert structure owing to vibration. Therefore, field blasting and vibration tests were performed on the blasting engineering of the Wuhan Metro Line 8 connected aisle, and the LS-DYNA software was used to analyze the dynamic response characteristics of an underground drainage box culvert during the blasting test. The vibration response evolution law of the buried drainage box culvert under blasting vibration was investigated, and a safe surface control standard for the blast vibration of a drainage box culvert is proposed. The results reveal that the maximum tensile stress of the box culvert structure was 0.33 MPa. The peak particle velocity (PPV) and peak tensile stress (PTS) of the drainage box culvert decreased as the water level in the box culvert increased. Based on the relationship between the tensile stress of the box culvert, PPV of the box culvert, and PPV of the surface, it is proposed that the surface control velocity of the buried drainage box culvert is 1.36 cm/s.
The curing temperature-dependent cement hydration causes the nonlinear evolution of fracture behavior and properties of fiber-reinforced cemented paste backfill (CPB) and thus influences the stability of mine backfill materials in deep mines. Therefore, the coupled effect of curing temperature (20, 35, and 45 °C) and cement hydration at different curing times (3, 7, and 28 d) on the mode-I and mode-II fracture behavior and properties of fiber-reinforced CPB is investigated. A comprehensive experimental testing program consisting of semicircular bend tests, direct shear tests, measurement of volumetric water content and matric suction, TG/DTG tests, and SEM observation is carried out. The results show that the coupled thermochemical effect results in strongly nonlinear development of pre- and post-peak behavior of fiber-reinforced CPB. Moreover, the results discover a positive linear correlation between fracture toughness and shear strength parameters and also reveal the vital role played by matric suction in the formation of fracture toughness. Furthermore, predictive functions are developed to estimate the coupled thermochemical effect on the development of KIc and KIIc. Therefore, the findings and the developed mathematical tools have the potential to promote the successful application of fiber-reinforced CPB technology in deep underground mines.
An analytical model is proposed to estimate the discontinuous mechanical behavior of an existing shield tunnel above a new tunnel. The existing shield tunnel is regarded as a Timoshenko beam with longitudinal joints. The opening and relative dislocation of the longitudinal joints can be calculated using Dirac delta functions. Compared with other approaches, our method yields results that are consistent with centrifugation test data. The effects of the stiffness reduction at the longitudinal joints (α and β), the shearing stiffness of the Timoshenko beam GA, and different additional pressure profiles on the responses of the shield tunnel are investigated. The results indicate that our proposed method is suitable for simulating the discontinuous mechanical behaviors of existing shield tunnels with longitudinal joints. The deformation and internal forces decrease as α, β, and GA increase. The bending moment and shear force are discontinuous despite slight discontinuities in the deflection, opening, and dislocation. The deflection curve is consistent with the additional pressure profile. Extensive opening, dislocation, and internal forces are induced at the location of mutation pressures. In addition, the joints allow rigid structures to behave flexibly in general, as well as allow flexible structures to exhibit locally rigid characteristics. Owing to the discontinuous characteristics, the internal forces and their abrupt changes at vulnerable sections must be monitored to ensure the structural safety of existing shield tunnels.
This study aimed to investigate a novel slender buckling-restrained knee brace damper (BRKB) for welded and weld-free steel framing systems. The proposed BRKB adopts steel bar cores connected by a central coupler and restrained by tube buckling restrainers with a cover tube supporter. The advantages of the proposed damper include easy assembly compared to conventional buckling restrained braces, and high architectural flexibility for the retrofitting of large-span weld-free or welded steel moment-resisting systems. Specifically, by increasing the number of contraction allowances, undesirable failure mechanisms that are global instability and local buckling of the restrainer ends can be effectively suppressed because the more uniform plastic deformation of the core bar can be achieved longitudinally. In this study, displacement-controlled compression and cyclic loading tests were carried out to investigate the deformation capacities of the proposed BRKBs. Structural performance metrics associated with both loading tests, such as strength capacities, strains at the cover tubes and buckling restrainers, and hysteretic behaviors of the proposed damper under cyclic loads, were measured and discussed. Test results revealed that the geometrical characteristics of the cover tubes and adopted contraction allowances at the dampers play essential roles in their load-bearing capacities.
The objective of the current study is to propose an expert system framework based on a supervised machine learning technique (MLT) to predict the seismic performance of low- to mid-rise frame structures considering soil-structure interaction (SSI). The methodology of the framework is based on examining different MLTs to obtain the highest possible accuracy for prediction. Within the MLT, a sensitivity analysis was conducted on the main SSI parameters to select the most effective input parameters. Multiple limit state criteria were used for the seismic evaluation within the process. A new global seismic assessment ratio was introduced that considers both serviceability and strength aspects by utilizing three different engineering demand parameters (EDPs). The proposed framework is novel because it enables the designer to seismically assess the structure, while simultaneously considering different EDPs and multiple limit states. Moreover, the framework provides recommendations for building component design based on the newly introduced global seismic assessment ratio, which considers different levels of seismic hazards. The proposed framework was validated through comparison using non-linear time history (NLTH) analysis. The results show that the proposed framework provides more accurate results than conventional methods. Finally, the generalization potential of the proposed framework was tested by investigating two different types of structural irregularities, namely, stiffness and mass irregularities. The results from the framework were in good agreement with the NLTH analysis results for the selected case studies, and peak ground acceleration (PGA) was found to be the most influential input parameter in the assessment process for the case study models investigated. The proposed framework shows high generalization potential for low- to mid-rise structures.
Thermal energy storage recycled powder mortar (TESRM) was developed in this study by incorporating paraffin/recycled brick powder (paraffin/BP) composite phase change materials (PCM). Fourier transform infrared and thermogravimetric analysis results showed that paraffin/BP composite PCM had good chemical and thermal stability. The onset melting temperature and latent heat of the composite PCM were 46.49 °C and 30.1 J·g−1. The fresh mortar properties and hardened properties were also investigated in this study. Paraffin/BP composite PCM with replacement ratio of 0%, 10%, 20%, and 30% by weight of cement were studied. The results showed that the static and dynamic yield stresses of TESRM were 699.4% and 172.9% higher than those of normal mortar, respectively. The addition of paraffin/BP composite PCM had a positive impact on the mechanical properties of mortar at later ages, and could also reduce the dry shrinkage of mortar. The dry shrinkage of TESRM had a maximum reduction about 26.15% at 120 d. The thermal properties of TESRM were better than those of normal mortar. The thermal conductivity of TESRM was 36.3% less than that of normal mortar and the heating test results showed that TESRM had good thermal energy storage performance.
The integrity and bearing capacity of segment joints in shield tunnels are associated closely with the mechanical properties of the joints. This study focuses on the mechanical characteristics and mechanism of a bolted circumferential joint during the entire bearing process. Simplified analytical algorithms for four stress stages are established to describe the bearing behaviors of the joint under a compressive bending load. A height adjustment coefficient, α, for the outer concrete compression zone is introduced into a simplified analytical model. Factors affecting α are determined, and the degree of influence of these factors is investigated via orthogonal numerical simulations. The numerical results show that α can be specified as approximately 0.2 for most metro shield tunnels in China. Subsequently, a case study is performed to verify the rationality of the simplified theoretical analysis for the segment joint via numerical simulations and experiments. Using the proposed simplified analytical algorithms, a parametric investigation is conducted to discuss the factors affecting the ultimate compressive bending capacity of the joint. The method for optimizing the joint flexural stiffness is clarified. The results of this study can provide a theoretical basis for optimizing the design and prediciting the damage of bolted segment joints in shield tunnels.
The horizontal bearing behavior of a single batter pile (SBP) is vital to its application in practical engineering; however, the horizontal responses of SBPs change with the directions of horizontal loads, and this phenomenon is rarely investigated. Therefore, the directional differences in the horizontal bearing behaviors of SBPs are investigated in this study. Four model tests are conducted to preliminarily examine the effects of the skew angle of horizontal loads on the horizontal bearing capacities and distributions of the bending moments of the SBPs. Subsequently, the differences in the responses of the SBPs under horizontal loads in various directions at full scale are analyzed comprehensively via finite-element (FE) analysis. The effects of the skew angle on SBP-soil interaction are discussed. Moreover, an empirical design method is proposed based on the FE analysis results to predict the bearing ratios of SBPs in medium-dense and dense sand while considering the effects of the skew angle, batter angle, and pile diameter. The method is confirmed to be effective, as confirmed by the close agreement between the predicting results with the model test (reported in this study) and centrifuge model test results (reported in the literature).
Textile reinforced mortar is widely used as an overlay for the repair, rehabilitation, and retrofitting of concrete structures. Recently, textile reinforced concrete has been identified as a suitable lining material for improving the durability of existing concrete structures. In this study, we developed a textile-reinforced mortar mix using river sand and evaluated the different characteristics of the textile-reinforced mortar under various exposure conditions. Studies were carried out in two phases. In the first phase, the pullout strength, temperature resistance, water absorption, and compressive and bending strength values of three different textile-reinforced mortar mixes with a single type of textile reinforcement were investigated. In the second phase, the chemical resistance of the mix that showed the best performance in the abovementioned tests was examined for use as an overlay for a concrete substrate. Investigations were performed on three different thicknesses of the textile reinforced mortar overlaid on concrete specimens that were subjected to acidic and alkaline environments. The flexural responses and degradations of the textile reinforced mortar overlaid specimens were examined by performing bending tests. The experimental findings indicated the feasibility of using textile reinforced mortar as an overlay for durable concrete construction practices.
Multilayered nanoscale structures are used in several applications. Because the effect of surface energy becomes nontrivial at such a small scale, a modified continuum theory is required to accurately predict their mechanical behaviors. A Gurtin–Murdoch continuum model of surface elasticity is implemented to establish a computational scheme for investigating an elastic multilayered system under axisymmetric loads with the incorporation of surface/interface energy. Each layer stiffness matrix is derived based on the general solutions of stresses and displacements obtained in the form of the Hankel integral transform. Numerical solutions to the global equation, which are formulated based on the continuity conditions of tractions and displacements across interfaces between layers, yield the displacements at each layer interface and on the top surface of the multilayered medium. The numerical solutions indicate that the elastic responses of multilayered structures are affected significantly by the surface material properties of both the top surface and interfaces, and that they become size dependent. In addition, the indentation problem of a multilayered nanoscale elastic medium under a rigid frictionless cylindrical punch is investigated to demonstrate the application of the proposed solution scheme.
Due to recent advances in the field of artificial neural networks (ANN) and the global sensitivity analysis (GSA) method, the application of these techniques in structural analysis has become feasible. A connector is an important part of a composite beam, and its shear strength can have a significant impact on structural design. In this paper, the shear performance of perfobond rib shear connectors (PRSCs) is predicted based on the back propagation (BP) ANN model, the Genetic Algorithm (GA) method and GSA method. A database was created using push-out test test and related references, where the input variables were based on different empirical formulas and the output variables were the corresponding shear strengths. The results predicted by the ANN models and empirical equations were compared, and the factors affecting shear strength were examined by the GSA method. The results show that the use of ANN model optimization by GA method has fewer errors compared to the empirical equations. Furthermore, penetrating reinforcement has the greatest sensitivity to shear performance, while the bonding force between steel plate and concrete has the least sensitivity to shear strength.
In this study, a novel diagonally inserted bar-type basalt fiber reinforced polymer (BFRP) connector was proposed, aiming to achieve both construction convenience and partially composite behavior in precast concrete sandwich panels (PCSPs). First, pull-out tests were conducted to evaluate the anchoring performance of the connector in concrete after exposure to different temperatures. Thereafter, direct shear tests were conducted to investigate the shear performance of the connector. After the test on the individual performance of the connector, five façade PCSP specimens with the bar-type BFRP connector were fabricated, and the out-of-plane flexural performance was tested under a uniformly distributed load. The investigating parameters included the panel length, opening condition, and boundary condition. The results obtained in this study primarily indicated that 1) the bar-type BFRP connector can achieve a reliable anchorage system in concrete; 2) the bar-type BFRP connector can offer sufficient stiffness and capacity to achieve a partially composite PCSP; 3) the boundary condition of the panel considerably influenced the out-of-plane flexural performance and composite action of the investigated façade PCSP.
The aim of this study is to appraise the potential of calcium sulfoaluminate (CSA) cement-based grouts in simulated permafrost environments. The hydration and performance of CSA cement-based grouts cured in cold environments (10, 0, and −10 °C) are investigated using a combination of tests, including temperature recording, X-ray diffraction (XRD) tests, thermogravimetric analysis (TGA), and unconfined compressive strength (UCS) tests. The recorded temperature shows a rapid increase in temperature at the early stage in all the samples. Meanwhile, results of the TGA and XRD tests show the generation of a significant quantity of hydration products, which indicates the rapid hydration of CSA cement-based grouts at the early stage at low temperatures. Consequently, the CSA cement-based grouts exhibit remarkably high early strength. The UCS values of the samples cured for 2 h at −10, 0, and 10 °C are 6.5, 12.0, and 12.3 MPa, respectively. The UCS of the grouts cured at −10, 0, and 10 °C increases continuously with age and ultimately reached 14.9, 19.0, and 30.6 MPa at 28 d, respectively. The findings show that the strength of grouts fabricated using CSA cement can develop rapidly in cold environments, thus rendering them promising for permafrost applications.
This study focuses on the bending failure performance of a shield tunnel segment. A full-scale test was conducted to investigate deformation and failure characteristics. During the loading, the bending failure process can be divided into four stages: the elastic stage, working stage with cracks, failure stage, and ultimate stage. The characteristic loads between contiguous stages are the cracking, failure, and ultimate loads. A numerical model corresponding to the test was established using the elastoplastic damage constitutive model of concrete. After a comparative analysis of the simulation and test results, parametric studies were performed to discuss the influence of the reinforcement ratio and proportion of tensile longitudinal reinforcement on the bearing capacity. The results indicated that the change in the reinforcement ratio and the proportion of tensile longitudinal reinforcement had little effect on the cracking load but significantly influenced the failure and ultimate loads of the segment. It is suggested that in the reinforcement design of the subway segment, the reinforcement ratio and the proportion of tensile longitudinal reinforcement can be chosen in the range of 0.7%–1.2% and 49%–55%, respectively, allowing the segment to effectively use the reinforcement and exert the design strength, thereby improving the bearing capacity of the segment.
In this study, the mechanical properties of the composite plate were considered Gaussian random fields and their effects on the buckling load and corresponding mode shapes were studied by developing a semi-analytical non-intrusive approach. The random fields were decomposed by the Karhunen−Loève method. The strains were defined based on the assumptions of the first-order and higher-order shear-deformation theories. Stochastic equations of motion were extracted using Euler–Lagrange equations. The probabilistic response space was obtained by employing the non-intrusive polynomial chaos method. Finally, the effect of spatially varying stochastic properties on the critical load of the plate and the irregularity of buckling mode shapes and their sequences were studied for the first time. Our findings showed that different shear deformation plate theories could significantly influence the reliability of thicker plates under compressive loading. It is suggested that a linear relationship exists between the mechanical properties’ variation coefficient and critical loads’ variation coefficient. Also, in modeling the plate properties as random fields, a significant stochastic irregularity is obtained in buckling mode shapes, which is crucial in practical applications.
Clear asphalt (CA) currently used in light-colored asphalt mixtures (LCAM) exhibits poor transparency and adhesion. Therefore, a highly transparent CA (HCA) modified using a silane coupling agent (KH550) was prepared. Furthermore, LCAM was prepared by mixing CA and limestone aggregates. The properties of the HCA and ordinary CA (OCA) were characterized using conventional asphalt tests, optical tests, pull-off tests, ultraviolet aging tests, dynamic shear rheometry, Fourier-transform infrared spectroscopy, differential scanning calorimetry, and scanning electron microscopy. Whereas Marshall, moisture resistance, wheel tracking, trabecular bending, and British pendulum tests were employed for the LCAM. The transmittance and spectral reflectance of the HCA were 123.30 and 3.74 times greater than those of the OCA, respectively. The complex modulus and viscosity-aging index of the HCA were 48% and 53% less than those of the OCA, respectively. After modification with KH550, the Marshall stability ratio, tensile strength ratio, and flexural strain of the HCA-prepared LCAM increased by 12.92%, 25.06%, and 23.90%, respectively. However, the rutting resistance of the HCA-prepared LCAM was 14.3% less than that of the OCA-prepared LCAM. The comprehensive performances of the HCA and HCA-prepared LCAM were 49.2% and 10.3% greater than those of the OCA and OCA-prepared LCAM, respectively, indicating a high application value in the future.